Knowledge Forest
MCPB · KNOWLEDGE-FOREST-MCP.MCPB
Local-first personal knowledge and learning memory for AI tutors with evidence-gated mastery.
Available components
Last scanned (3 hours ago)
Scores higher than 94% of MCPB servers
Category Memory and Knowledge
How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →
Supply Chain Security25
- No malware scan is available for this kind of package: the supply-chain vendors we use do not cover it. This is a permanent gap in our coverage, not a finding about the package.Unverified
- Known CVEs were checked across the 3 of 3 dependencies we could resolve, so this covers what we could see, not the whole tree.Partial
- No install/post-install scripts declared.Pass
- 0 of 3 dependencies flagged as unhealthy. View diagnostics → Pass
Provenance & Transparency48
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
- Clear OSI-approved license (Apache-2.0).Pass
- Actively maintained (last published 22 days ago).Pass
- Publishes a security disclosure policy (SECURITY.md).Pass
Schema Quality & AI Usability80
- 100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).Pass
- AI-judged instruction clarity (good).Pass
- Tool/resource definitions use about 665 tokens (~66/item across 10 items; 10 tools + 0 resources), lean.Pass
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management77
- Stability observed for 23 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage68
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 4% of tool parameters carry a description.Partial
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 10 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 11 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a current MCP spec version (2026-07-28).Pass
Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 17 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 73 to 77. That category is still filling its 30-day observation window: 22 days of observed history at the previous scan, 23 at this one. The score rises as the window fills, whether or not the server changes.
- 15 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 67 to 70. That category is still filling its 30-day observation window: 20 days of observed history at the previous scan, 21 at this one. The score rises as the window fills, whether or not the server changes.
- 13 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 60 to 63. That category is still filling its 30-day observation window: 18 days of observed history at the previous scan, 19 at this one. The score rises as the window fills, whether or not the server changes.
- 12 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 53 to 60. That category is still filling its 30-day observation window: 16 days of observed history at the previous scan, 18 at this one. The score rises as the window fills, whether or not the server changes.
- 10 Oct 26 +2
No change was recorded against any check on this day. Stability & Change Management went from 33 to 53. That category is still filling its 30-day observation window: 10 days of observed history at the previous scan, 16 at this one. The score rises as the window fills, whether or not the server changes.
- 4 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 30 to 33. That category is still filling its 30-day observation window: 9 days of observed history at the previous scan, 10 at this one. The score rises as the window fills, whether or not the server changes.
- 2 Oct 26 +4
- Stability: unverified → 0.27 ▲ functional
- 28 Sept 26 0
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 17 Oct 2026 · Analysed mcpb/https://github.com/znecho9/knowledge-forest-mcp/releases/download/v0.1.1/knowledge-forest-mcp.mcpb
Provenance No attestation
The registry publishes no build provenance for this version, so there is nothing to verify.
| Result | No attestation |
|---|---|
| Ecosystem | mcpb |
| Reason | No attestation published |
Background: How many MCP packages publish verified provenance →
Dependencies 3 packages
| Packages resolved | 3 |
|---|---|
| Tree resolution | Complete |
Background: SBOMs and build attestations, explained →
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
append_learning_note Append a learning record ~68
Append a note, reflection, source, or exercise to a node. Source-visible material never changes mastery state.
| Name | Type | Req | Description |
|---|---|---|---|
| content | string | yes | – |
| kind | string | yes | – |
| node_id | string | yes | – |
| source_visibility | string | yes | – |
| sources | array | – | – |
No output schema declared.
No examples provided.
create_goal_tree Create a minimal sufficient goal tree ~51
Persist one observable goal, its branches, and prerequisite-linked knowledge nodes. Search first. Use reuse_node_id only for truly equivalent existing concepts.
| Name | Type | Req | Description |
|---|---|---|---|
| branches | array | yes | – |
| goal | object | yes | – |
No output schema declared.
No examples provided.
diagnose_node Diagnose a knowledge node ~41
Deterministically identify prerequisite, depth, and evidence gaps and recommend the next learning action. It does not call a model.
| Name | Type | Req | Description |
|---|---|---|---|
| node_id | string | yes | – |
No output schema declared.
No examples provided.
export_forest Export the complete forest ~24
Read the complete portable forest state, including append-only learning records and evidence.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
forest_overview View knowledge forest overview ~47
Read goals, mastery counts, and the next ready knowledge nodes. Call this first; it never modifies learning state.
| Name | Type | Req | Description |
|---|---|---|---|
| goal_id | string | – | Optional goal ID to scope the overview. |
No output schema declared.
No examples provided.
get_learning_queue Get the actionable learning queue ~38
Return ready and prerequisite-blocked nodes, ordered by readiness and importance.
| Name | Type | Req | Description |
|---|---|---|---|
| goal_id | string | – | – |
| limit | integer | – | – |
No output schema declared.
No examples provided.
get_node_context Get complete node context ~41
Read a knowledge node, its goal memberships, prerequisites, dependents, learning entries, verification history, and deterministic diagnosis.
| Name | Type | Req | Description |
|---|---|---|---|
| node_id | string | yes | – |
No output schema declared.
No examples provided.
record_verification Record closed-book mastery evidence ~95
Record one verification attempt. Mastery advances only for demonstrated, novel, unassisted, closed-book performance; the server computes acceptance.
| Name | Type | Req | Description |
|---|---|---|---|
| assisted | boolean | yes | – |
| closed_book | boolean | yes | – |
| node_id | string | yes | – |
| novel_prompt | boolean | yes | – |
| outcome | string | yes | – |
| prompt | string | yes | – |
| rationale | string | yes | – |
| response | string | yes | – |
No output schema declared.
No examples provided.
search_knowledge Search knowledge nodes ~41
Search canonical nodes before creating a goal tree. Results include reuse context and current mastery state.
| Name | Type | Req | Description |
|---|---|---|---|
| limit | integer | – | – |
| query | string | yes | – |
No output schema declared.
No examples provided.
update_node_learning_state Update learning depth or workflow state ~65
Set a learner-selected depth or non-verified workflow state. This tool cannot mark mastery; use record_verification for that.
| Name | Type | Req | Description |
|---|---|---|---|
| desired_depth | string | – | – |
| node_id | string | yes | – |
| reason | string | yes | – |
| status | string | – | – |
No output schema declared.
No examples provided.
How do I install the Knowledge Forest MCP server?
Knowledge Forest ships as an MCPB bundle, a single file you download and open in an MCP host that supports MCPB bundles, such as Claude Desktop. The host reads the launch command from the bundle's own manifest, so there is no command to copy. The MCP registry declares no SHA-256 for this bundle, so there is no published digest to check the download against.
mcpb · knowledge-forest-mcp.mcpb
Download bundleThe MCP registry declares no SHA-256 for this bundle, so there is no published digest to check it against. Open it with an MCPB-capable host such as Claude Desktop.
What is the Knowledge Forest MCP server?
Knowledge Forest is an MCP server listed in the public MCP registry as io.github.znecho9/knowledge-forest-mcp. Local-first personal knowledge and learning memory for AI tutors with evidence-gated mastery. This page covers its MCPB bundle (https://github.com/znecho9/knowledge-forest-mcp/releases/download/v0.1.1/knowledge-forest-mcp.mcpb).
Is the Knowledge Forest MCP server safe to use?
Knowledge Forest scores 58 out of 100 on VerifyMCP. It declares no install or post-install scripts. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.
What tools does the Knowledge Forest MCP server expose?
Knowledge Forest exposes 10 tools: forest_overview, search_knowledge, get_node_context, create_goal_tree, update_node_learning_state, and 5 more. Their descriptions and schemas cost roughly 511 tokens of context every time the server is loaded.
What licence is the Knowledge Forest MCP server under?
Knowledge Forest declares the Apache-2.0 licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.